Concealed damage (CD) in raw almonds (Prunus dulcis (Mill.) D. A. Webb) is defined by the industry as a brown discoloration of the kernel interior (nutmeat) that appears only after moderate to high heat treatment (e.g. blanching, drying, roasting, etc.) as shown in FIG. 1. CD may develop anytime during harvest when rain occurs, or after harvest when kernels are in windrows or stockpiles and exposed to warm and moist environments (1,2). Raw almond kernels with CD, have no visible defects on the interior or exterior surface of the kernel. Additionally, there are no visible signs of CD on the surface of whole roasted kernels (3). CD is frequently associated with a strong bitter flavor(s) that can result in immediate consumer rejection (1). Currently there are no screening methods available for detecting CD in raw almonds, or other nuts affected by CD, and processors often do not realize nuts are damaged until after they have been roasted (1). Under current production practices, the most common methods for detecting CD involve visual inspection of roasted almonds after they are split open. Kernels with a “dark brown” color over ˜50% of the interior of the kernel are considered to have CD (4). A similar approach is used for hazelnuts (5). Visual inspection and manual sorting is time-consuming, subjective, labor intensive and cannot be used to identify nuts with CD before heat treatments. This can result in significant product loss.
The current hypothesis is that the browning associated with CD is related to the Maillard reaction. Moisture can induced the hydrolysis of carbohydrates and potential availability of reducing sugars for Maillard browning reactions. For example, in macadamia nuts exposed to moisture during harvesting, increased levels of reducing sugars were observed in nuts with internal browning (6). Similar observations were made in hazelnuts (7) and in almonds exposed to simulated rainfall (2). In more recent studies, elevated levels of volatiles related to lipid oxidation and amino acid degradation were observed in almonds with CD (8). Both lipid oxidation products and protein degradation products can serve as reactants in the Maillard browning reaction.
Near-infrared spectroscopy (NIR) is a rapid and effective method for screening foods for specific chemical and physical characteristics (9). NIR is advantageous as a screening method as it is non-destructive, can be used on whole foods, and produces no waste. The NIR spectral region (720 to 2500 nm) is ideally suited for foods as it contains absorbance bands that result primarily from three chemical bonds: C—H (fats, oil, hydrocarbons), O—H (water, alcohol) and N—H (protein). NIR spectroscopy is increasingly considered one of the more promising in-line detection methods for rapidly measuring specific chemical properties of food.6 It has been successfully applied in detecting quality defects in macadamia kernels (7), walnuts (10), chestnuts (11-12), hazelnuts (13-14), and soybean seed (15). It has also been employed for food composition analysis including oleic and linoleic acid content in peanut seed (16), acidity and water content in hazelnuts (17), and characterization of shea tree nut fat profiles (18).
Pearson (1999) was the first to recognize the use of NIR spectroscopy for the identification of CD in raw almonds (4, 19) and evaluated the transmission spectrum from 700-1400 nm in almonds soaked in water, and dried but not roasted. In these studies, almonds were either soaked for 30 minutes and exposed to 95% relative humidity for 30 hours (short moisture), or soaked for 60 minutes and exposed to 95% relative humidity for 60 hours (long moisture). Almonds were then dried at either 55 or 110° C. The higher temperature and shorter soak times produced the greatest amount of CD. Almonds with CD had enhanced absorption at 930 nm (oil absorption band). Raw almonds with CD could be distinguished from normal almonds at an error of 12.4% by using principal components of the absorbance, first derivative and second derivative spectra between 1000-1300 nm. Pearson (1999) recognized that collecting the NIR spectra over the full transmission range would be too slow to achieve desired inspection rates of 40 nuts/s and therefore tested the feasibility of using just 6 light emitting diodes at 660, 830, 880, 890, 940, and 950 nm (19). These data resulted in a classification error rate of 14.3% for the validation set. More recently, Nakariyakul (20-21) achieve a higher classification rate using hyperspectral transmission and focusing on a sub-set of absorbing bands (760, 920, 935, and 970 nm) with a false negative error rate of 14.81%. Almonds used in this study were generated by Pearson (1999) as described above.